AI RESEARCH
MyoSem: Aligning Electromyography to Natural-Language Action Semantics for Hand Action Understanding
arXiv CS.AI
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ArXi:2606.00174v1 Announce Type: cross Electromyography (EMG) directly reflects muscle activation and is a key sensing modality for gesture recognition, prosthetic control, and wearable interaction. Existing EMG methods, however, commonly formulate hand action understanding as classification over fixed labels, making it difficult to querying, retrieval, and generalization based on action descriptions. We present MyoSem, an EMG--action semantic alignment framework that maps low-level EMG signals into a shared semantic space constructed from multi-view action descriptions.